Utility to launch a dask.distributed cluster on a UGE scheduler
The typical dask.distributed audience has a budget and access to whole
[virtual] machines via cloud providers. Academics, on the other hand,
may be restricted to a dedicated cluster where single slots can only be
captured for a limited time, and the nodes may be hidden behind layers of
inbound firewalls in interesting ways. dask-uge runs a dask-scheduler
on an execution node, forwards connections from the submission host to the
scheduler, and then keeps a pool of workers running, submitting new
ones as jobs are killed for exceeding their allotted time. In addition,
a short shell snippet can be included to initialize the environment on
the node (e.g. setting up a virtualenv) before the scheduler or worker
runs, in case the local UGE configuration makes it difficult to cleanly
forward the environment from the submission host.
dask-uge.py --nworkers 10
At the moment, dask-uge uses the default ports for dask-scheduler, and
the environment setup portion and job resource requests are hard-coded.